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Optical Remote Sensing

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Cover of 'Optical Remote Sensing'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Hyperspectral Data Compression Tradeoff
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    Chapter 3 Reconstructions from Compressive Random Projections of Hyperspectral Imagery
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    Chapter 4 Integrated Sensing and Processing for Hyperspectral Imagery
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    Chapter 5 Color Science and Engineering for the Display of Remote Sensing Images
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    Chapter 6 An Evaluation of Visualization Techniques for Remotely Sensed Hyperspectral Imagery
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    Chapter 7 A Divide-and-Conquer Paradigm for Hyperspectral Classification and Target Recognition
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    Chapter 8 The Evolution of the Morphological Profile: from Panchromatic to Hyperspectral Images
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    Chapter 9 Decision Fusion of Multiple Classifiers for Vegetation Mapping and Monitoring Applications by Means of Hyperspectral Data
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    Chapter 10 A Review of Kernel Methods in Remote Sensing Data Analysis
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    Chapter 11 Exploring Nonlinear Manifold Learning for Classification of Hyperspectral Data
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    Chapter 12 Recent Developments in Endmember Extraction and Spectral Unmixing
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    Chapter 13 Change Detection in VHR Multispectral Images: Estimation and Reduction of Registration Noise Effects
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    Chapter 14 Effects of the Spatial Enhancement of Hyperspectral Images on the Distribution of Spectral Classes
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    Chapter 15 Fusion of Optical and SAR Data for Seismic Vulnerability Mapping of Buildings
Attention for Chapter 3: Reconstructions from Compressive Random Projections of Hyperspectral Imagery
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Chapter title
Reconstructions from Compressive Random Projections of Hyperspectral Imagery
Chapter number 3
Book title
Optical Remote Sensing
Published by
Springer, Berlin, Heidelberg, January 2011
DOI 10.1007/978-3-642-14212-3_3
Book ISBNs
978-3-64-214211-6, 978-3-64-214212-3
Authors

James E. Fowler, Qian Du

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